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Circular cones are a new class of regular cones that include the well-known second-order cones as a special case. In this paper, we study the algebraic structure of the circular cone and show that based on the standard inner product this cone is nonsymmetric while using the new-defined circular inner product this cone not only is symmetric but also the algebra associated with it, is a Euclidean Jordan algebra. Then, using the machinery of Euclidean Jordan algebras and the Nestrov–Todd search directions, we propose a primal-dual path-following interior-point algorithm for linear complementarity problems over the Cartesian product of the circular cones. The convergence analysis of the algorithm is shown and it is proved that this class of mathematical problems is polynomial-time solvable.

In this paper, we propose an infeasible interior-point algorithm for symmetric optimization problems using a new wide neighborhood and estimating the central path by an ellipse. In contrast of most interior-point algorithms for symmetric optimization which search an $\varepsilon$ -optimal solution of the problem in a small neighborhood of the central path, our algorithm searches for optimizers in a new wide neighborhood of the ellipsoidal approximation of central path. The convergence analysis of the algorithm is shown and it is proved that the iteration bound of the algorithm is $O ( r\log\varepsilon^{-1} ) $ which improves the complexity bound of the recent proposed algorithm by Liu et al. (J. Optim. Theory Appl., 2013, https://doi.org/10.1007/s10957-013-0303-y ) for symmetric optimization by the factor $r^{\frac{1}{2}}$ and matches the currently best-known iteration bound for infeasible interior-point methods.

Liposomal nanoparticles are the most commonly used drug nano-delivery platforms. However, recent reports show that certain pegylated liposomal nanoparticles (PLNs) and polymeric nanoparticles have the potential to enhance tumor growth and inhibit antitumor immunity in murine cancer models. We sought herein to identify the mechanisms and determine whether PLN-associated immunosuppression and tumor growth can be reversed using alendronate, an immune modulatory drug. By conducting in vivo and ex vivo experiments with the immunocompetent TC-1 murine tumor model, we found that macrophages were the primary cells that internalized PLN in the tumor microenvironment and that PLN-induced tumor growth was dependent on macrophages. Treatment with PLN increased immunosuppression as evidenced by increased expression of arginase-1 in CD11b+Gr1+ cells, diminished M1 functionality in macrophages, and globally suppressed T-cell cytokine production. Encapsulating alendronate in PLN reversed these effects on myeloid cells and shifted the profile of multi-cytokine producing T-cells towards an IFNγ+ perforin+ response, suggesting increased cytotoxic functionality. Importantly, we also found that PLN-encapsulated alendronate (PLN-alen), but not free alendronate, abrogated PLN-induced tumor growth and increased progression-free survival. In summary, we have identified a novel mechanism of PLN-induced tumor growth through macrophage polarization and immunosuppression that can be targeted and inactivated to improve the anticancer efficacy of PLN-delivered drugs. Importantly, we also determined that PLN-alen not only reversed protumoral effects of the PLN carrier, but also had moderate antitumor activity. Our findings strongly support the inclusion of immune-responsive tumor models and in-depth immune functional studies in the preclinical drug development paradigm for cancer nanomedicines, and the further development of chemo-immunotherapy strategies to co-deliver alendronate and chemotherapy for the treatment of cancer.

In this paper, we propose an arc-search infeasible-interior-point method based on the wide neighbourhood for linear complementarity problems over symmetric cones with the Cartesian -property (-SCLC...

In this paper, a wide-neighborhood predictor-corrector feasible interior-point algorithm for linear complementarity problems is proposed. The algorithm is based on using the classical affine scaling direction as a part in a corrector step, not in a predictor step. The convergence analysis of the algorithm is shown, and it is proved that the algorithm has the polynomial complexity $$O\left(\sqrt{n}\log \varepsilon ^{-1}\right)$$ which coincides with the best known iteration bound for this class of mathematical problems. The numerical results indicate the efficiency of the algorithm.

The morphology and crystallization behavior of blends of polypropylene (PP) and an ethylene-based thermoplastic elastomer (TPO) were investigated by scanning electron microscopy (SEM) and differential scanning calorimetry (DSC). The SEM images showed a two-phase morphology for these blends. As TPO was partially crystalline, two distinct peaks were observed in both heating and cooling scans of DSC. The crystallization temperature of TPO in blends was higher than pure TPO. In contrast, the crystallization temperature of PP in blends was lower than pure PP. The crystallization behavior of blends was modeled by Avrami equation. It was observed that the presence of TPO accelerated the growth rate of crystals of PP in PP/TPO blends.

In this paper, we generalize Darvay’s technique for linear programming to horizontal linear complementarity problem over the Cartesian product of symmetric cones, or briefly Cartesian -SCHLCP, using Euclidean Jordan algebras. This problem is a comprehensive optimization problem over symmetric cones, so that handling this problem removes the necessity of dealing with many other ones. This paper is among the first ones which study interior point methods (IPMs) for the generic Cartesian -SCHLCP problems. The symmetrization of the search directions used in this paper is based on the Nesterov–Todd (NT) scaling scheme, and only full-NT steps are used at each iteration. So, line searches are not longer needed. The derived complexity bound matches the best obtained one for infeasible IPMs with small updates.

In this article, we present a corrector-predictor path-following interior-point algorithm for P∗(κ)-horizontal linear complementarity problem over Cartesian product of symmetric cones, using Euclidean Jordan algebras. This comprehensive problem is a newly introduced problem in the context of interior-point methods. The algorithm takes damped Nesterov-Todd steps in the predictor (affine-scaling) stage while maintaining a certain neighborhood of the central path. Moreover, at each corrector stage, we use only full-Nesterov-Todd steps. Furthermore, we derive the currently best known iteration bound for the algorithm with small updates, namely, , where r is the rank of the associated Euclidean Jordan algebra and 𝜀 is a prescribed tolerance.

Liner wear occurs during the grinding process in tumbling mill. It has a significant influence on the overall economic performance of mills. It will be worthwhile to know the effect of mill operating parameters on the liner wear intensity. In the present work, an experimental–theoretical procedure is presented for evaluation of the liner wear due to abrasion and impact. A wear tester is used to measure the wear of specimen due to ball impacts. A relation is then extracted which gives the wear of specimen at the different impact conditions. This relation is used to evaluate the impact liner wear. Abrasion liner wear is evaluated using the procedure suggested by Radziszewski. To have the experimental data, a laboratory mill is used. A small specimen is inserted in the liner face of the laboratory mill to measure its wear during the mill operation. The cataract regime in mill is eliminated by a mechanism to measure the impact and abrasion wear separately. The comparisons show the appropriate accordance of predicted and measured liner wear, so the model can be used to determine the impact and abrasion wear portions of mill liners.

In this work, the inverse analysis is applied to radiative heat transfer boundary design problems with non-gray media. The objective of the inverse problem is to find the power of the heaters on the heater surface that produces the desired output, that is, temperature and heat flux distribution over the design surface. The inverse problem is formulated as an optimization problem for minimization of an objective function, which is defined by the sum of the squared difference between estimated and desired heat flux distributions over the design surface. The non-gray optimization problem is solved using the conjugate gradient method, which is a gradient-based optimization method. The spectral line weighted-sum-of-gray-gases model (SLW) is used to account for non-gray gas radiation properties. The radiative transfer equation is solved by the discrete ordinates method combined with two models for simulation of non-gray media. Enclosures with diffuse and gray walls are considered. Radiation is assumed t...

A novel mathematical model for combustion of a single copper concentrate particle is presented. The model includes particle volatilization, fragmentation, smelting, and combustion phenomena. This model has been incorporated into a general computational fluid dynamics code to calculate flow field and particle trajectories needed to simulate the smelting process in flash furnaces. In this model, Lagrangian approach was used to handle solid particles and droplets of liquid fuel charged, while Eulerian framework was used to handle the gas phase flow field. The results show that the effect of particle fragmentation was remarkable in flash smelting process as compared with experimental data and should be considered in combustion modeling. Moreover, the flash smelting process simulation results show that the reaction shaft design should be optimized based on a combination of furnace dimension and type of concentrate burners.

In this paper, a full-Newton step infeasible kernel-based interior-point algorithm for solving monotone linear complementarity problems is proposed. In each iteration, the algorithm computes the new feasibility search directions by using a specific kernel function with the trigonometric barrier term and obtains the centering search directions using the classical kernel function. The algorithm takes only full-Newton steps and therefore no line-searches are needed for generating the new iterations. The convergence of the algorithm is shown and it is proved that the iteration bound of the algorithm coincides with the currently best iteration bound for monotone linear complementarity problem.

We investigate the effect of making equivalent transformation for the central path from $$x\diamond s=\mu e$$ to $$x\diamond s=\mu v$$ , and we obtain a new class of search directions in both version of feasible and infeasible interior point algorithms for linear optimization over Cartesian symmetric cones. We propose a new modified infeasible interior-point algorithm based on elimination of the centering steps. Moreover, the proposed algorithm finds an $$\varepsilon $$ -optimal solution of the underlying problem in polynomial time complexity and its iteration bound coincides with the best known iteration bound for this class of problems.

An inverse analysis is employed to control the time rate of heaters in a 2-D smelting furnace to provide the specified radiative heat flux across the design surface to establish a desired melting rate. The design surface in the smelting furnace is the melting surface of the metal concentrate bank, and the melting process is considered to occur as an ablation phenomenon. The net radiation method is used to determine the radiation exchange between the elements of the furnace surfaces and the melting surface. The conjugate gradient method is employed to minimize the objective function, which is the sum of square residuals between the estimated and the desired heat fluxes over the design surface. It is shown that the proposed inverse technique is reliable and accurate for predicting the heater power distribution.

In this paper, we propose a large-update primal–dual interior-point algorithm for second-order cone optimization (SOCO) based on a class of kernel functions consisting of a trigonometric barrier term. The algorithm starts from a strictly feasible point and generates a sequence of points converging to an optimal solution of the problem. Using a simple analysis, we show that the algorithm has worst case iteration complexity for large-update primal–dual interior point methods which coincides with the so far best-known iteration bound for SOCO.

We discovered that 90.3% of patients with angiomyolipomas, LAM, and tuberous sclerosis complex (TSC) carry the arginine variant of codon 72 (R72) of TP53 and that R72 increases the risk for angiomyolipoma. R72 transactivates NOTCH1 and NODAL better than the proline variant of codon 72 (P72), therefore, the expression of NOTCH1 and NODAL is increased in angiomyolipoma cells that carry R72. The loss of Tp53 and Tsc1 within nestin expressing cells in mice resulted in development of RCC with high Notch1 and Nodal expression suggesting that similar downstream mechanisms contribute to tumorigenesis as a result of p53 loss in mice and p53 polymorphism in humans. The loss of murine Tp53 or expression of human R72 contribute to tumorigenesis via enhancing epithelial-to-mesenchymal transition and motility of tumor cells through the Notch and Nodal pathways. IMPLICATIONS: This work revealed unexpected contributions of the p53 polymorphism to the pathogenesis of TSC and established signaling alterations caused by this polymorphism as a target for therapy. We found that the codon 72 TP53 polymorphism contributes to TSC-associated tumorigenesis via Notch and Nodal signaling.

An arc search interior-point algorithm for monotone symmetric cone linear complementarity problem is presented. The algorithm estimates the central path by an ellipse and follows an ellipsoidal approximation of the central path to reach an "-approximate solution of the problem in a wide neighborhood of the central path. The convergence analysis of the algorithm is derived. Furthermore, we prove that the algorithm has the complexity bound O ( p rL) using Nesterov-Todd search direction and O (rL) by the xs and sx search directions. The obtained iteration complexities coincide with the best-known ones obtained by any proposed interior- point algorithm for this class of mathematical problems.

In this article, we present a new predictor-corrector interior-point method, based on a wide neighborhood of the central path, for linear programming problems. In the corrector step ofthe proposed ...

In this paper, we present a path-following infeasible interior-point method for \(P_*(\kappa )\) horizontal linear complementarity problems (\(P_*(\kappa )\)-HLCPs). The algorithm is based on a simple kernel function for finding the search directions and defining the neighborhood of the central path. The algorithm follows the central path related to some perturbations of the original problem, using the so-called feasibility and centering steps, along with only full such steps. Therefore, it has the advantage that the calculation of the step sizes at each iteration is avoided. The complexity result shows that the full-Newton step infeasible interior-point algorithm based on the simple kernel function enjoys the best-known iteration complexity for \(P_*(\kappa )\)-HLCPs.

In this paper, we propose an infeasible-interior-point method, based on a new wide neighborhood of the central path, for linear complementarity problems over symmetric cones with the Cartesian $$P_*(\kappa )$$ -property. The convergence is shown for commutative class of search directions. Moreover, we analyze the algorithm and obtain the complexity bounds, which coincide with the best-known results for the Cartesian $$P_*(\kappa )$$ -SCLCPs. Some numerical tests are reported to illustrate our theoretical results.

Euclidean Jordan algebra is a commonly used tool in designing interior-point algorithms for symmetric cone programs. In this paper, we present a full Nesterov–Todd (NT) step infeasible interior-point algorithm for horizontal linear complementarity problems over Cartesian product of symmetric cones. Since the algorithm uses only full-NT feasibility and centring steps, it has the advantage that no line searches are needed. The complexity result obtained here for symmetric cones using NT directions coincides with the best bound obtained for horizontal linear complementarity problems.

Rank tests are known to be robust to outliers and violation of distributional assumptions. Two major issues besetting microarray data are violation of the normality assumption and contamination by outliers. In this article, we formulate the normal theory simultaneous tests and their aligned rank transformation (ART) analog for detecting differentially expressed genes. These tests are based on the least-squares estimates of the effects when data follow a linear model. Application of the two methods are then demonstrated on a real data set. To evaluate the performance of the aligned rank transform method with the corresponding normal theory method, data were simulated according to the characteristics of a real gene expression data. These simulated data are then used to compare the two methods with respect to their sensitivity to the distributional assumption and to outliers for controlling the family-wise Type I error rate, power, and false discovery rate. It is demonstrated that the ART generally possesses...

In this paper, we propose a primal–dual interior-point method for semidefinite optimization problems. The algorithm is based on a new class of search directions and the Ai-Zhang’s wide neighborhood for monotone linear complementarity problems. The theoretical complexity of the new algorithm is calculated. It is investigated that the proposed algorithm has polynomial iteration complexity \(O(\sqrt{n}L)\) and coincides with the best known iteration bound for semidefinite optimization problems.

This paper proposes a second-order Mehrotra-type predictor-corrector feasible interior-point algorithm for semidefinite optimization problems. In each iteration, the algorithm computes the Newton search directions through a new form of combination of the predictor and corrector directions. Using the Ai-Zhang wide neighborhood for linear complementarity problems, it is shown that the complexity bound of the algorithm is $O(\sqrt{n}\log \varepsilon^{-1})$ for the Nesterov-Todd search direction and $O({n}\log \varepsilon^{-1})$ for the Helmberg-Kojima-Monteiro search directions.

This paper contains an infeasible interior-point method for $$P_*(\kappa )$$ horizontal linear complementarity problem based on a kernel function. The kernel function is used to determine the search directions. These search directions differ from the usually used ones in some interior-point methods, and their analysis is more complicated. Main feature of our algorithm is that there is no calculation of the step size, i.e, we use full-Newton steps at each iteration. The algorithm constructs strictly feasible iterates for a sequence of perturbations of the given problem, close to its central path. Two types of full-Newton steps are used, feasibility steps and centering steps. The iteration bound matches the best-known iteration bound for these types of algorithms.

A mathematical model has been presented to study the combustion of a single copper concentrate particle with high moisture content. By using the presented model, the effect of particle moisture content on particle temperature, sulfur oxidation, and combustion heat generation has been evaluated. The mineralogical composition of the commonly used concentrate at Khatoonabad flash smelting furnace has been used in this study. It was found that the particle moisture content is removed in the sub-second time range and thus the moisture has marginal impact on the variation of particle temperature and on the reaction rate when the gas temperature is assumed to be constant in the reaction shaft. When a concentrate with high moisture content is charged, the particle size enlargement due to the agglomeration of concentrate particles causes an abrupt fall in the particle reaction rate.

Impact wear can be defined as the wear of a solid surface due to percussion, which is a repetitive exposure to dynamic contact by another solid body. It has not been studied as extensive as other wear mechanisms and the information on causes and actual data is quite scarce. In the present work an experimental wear tester is designed and used to study the impact wear phenomenon experimentally. It creates the consecutive impacts between balls and flat plate. The different ball sizes (up to 30 mm), impact velocities (up to 6 m.s-1) and impact angle (10°− 80°) can be tried by tester. The mass loss of plate is measured as the wear parameter. These measurements for different specimens revealed some aspects of their wearing behaviors. The obtained results could be helpful in optimal practical designs and explanation of some phenomena associated with impact wear.

Interior-Point Methods (IPMs) not only are the most effective methods in practice but also have polynomial-time complexity. Many researchers have proposed IPMs for Linear Optimization (LO) and achieved plentiful results. In many cases these methods were extendable for LO to Linear Complementarity Problems (LCPs) successfully. In this paper, motivated by the complexity results for linear optimization based on the study of H. Mansouri et al. (Mansouri and Zangiabadi in J. Optim. 62(2):285–297, 2013), we extend their idea for LO to LCP. The proposed algorithm requires two types of full-Newton steps are called, feasibility steps and (ordinary) centering steps, respectively. At each iteration both feasibility and optimality are reduced exactly at the same rate. In each iteration of the algorithm we use the largest possible barrier parameter value θ which lies between the two values \(\frac{1}{17n}\) and \(\frac{1}{13n}\), this makes the algorithm faster convergent for problems having a strictly complementarity solution.

Article history: Received May 22, 2013 Received in revised format 28 August 2013 Accepted 14 September 2013 Available online September 15 2013 This research proposes a comprehensive model that investigates the relationships between service quality, hedonic, perceived value and behavioral intentions. The purpose of this study is to build a better understanding of the determinants of customer satisfaction and customer loyalty throughout the restaurant services by incorporating the perceptions of hedonic effect in service delivery and outlining why and how service quality is important to customer satisfaction and customer loyalty. Respondents were chosen from three regular customers of Atawich chain restaurants in city of Tehran by using stratified random sampling method. A total of 390 questionnaires were used for data analysis. Structural equations modeling by using LISREL was performed to empirically test the relationships between the constructs of this study. Results show that both service quality and hedonic effect are importance predictors of customer satisfaction in Iranian society. In addition, results indicate that service quality and hedonic effect have positive and significant effects on perceived value. However, relationship between customer satisfaction and perceived value with attitudinal loyalty was not significant. Finally, it suggests that restaurant managers should improve their restaurant service offerings to satisfy customers. In addition, the results emphasize the significance of hedonic effect and positive emotions in creating perceived value and customer satisfaction.

A class of simultaneous tests based on the aligned rank transform (ART) statistics is proposed for linear functions of parameters in linear models. The asymptotic distributions are derived. The stability of the finite sample behaviour of the sampling distribution of the ART technique is studied by comparing the simulated upper quantiles of its sampling distribution with those of the multivariate t-distribution. Simulation also shows that the tests based on ART have excellent small sample properties and because of their robustness perform better than the methods based on the least-squares estimates.

mportance of the SAG (Semi Autogenous Grinding) mills for the mineral complexes persuades many researchers to study the behavior of these huge equipments. Laboratory mills and the DEM (Discrete element method) software are the prevalent and reliable methods of modeling the mill behaviors. The former is very costly and the latter not only takes the much time but also needs the very advanced computers. In the present work, a method is presented to predict the charge profile and shoulder and toe positions for a case study mill. Experimental relations are manipulated to determine the en masse geometry and the kinetic relations are used to explain the ball movement on the liner in order to determine the shoulder and toe positions. Model results have very good accordance with the experimental results obtained of a laboratory mill. The model is used to predict the load behavior of a SAG mill in the Sarcheshmeh copper complex in Iran. Acceptable results due to low cost and quickness make it as an appropriate method for predicting the charge profile in that tumbling mill.

The objective of this paper was to present a comprehensive analysis including analytical and numerical models which were developed to predict the performance of a solar chimney power plant in Kerman, Iran. The numerical model results including air temperature, velocity and electrical power output were validated by comparing with experimental data of the Manzanares prototype power plant. Also the mathematical model was verified with the practical power output of the Kerman pilot plant. Also in this paper, a novel approach to evaluate the influence of the site altitude on the potential of solar chimney power plants was presented and thereby a coefficient called altitude effectiveness was defined using Manzanares prototype geometrical parameters in different site altitudes. The developed model was applied to improve the performance of a solar chimney pilot power plant built in Kerman, Iran. Based on an approximate cost model, the thermo-economic optimal configurations of the pilot power plant were illustrated; and also it was found that the chimney diameter was the most important structural dimension to improve the performance of this pilot power plant.

Subcooled flow boiling of a nanofluid consisting of water and Al2O3 (dp = 30 nm) has been investigated numerically using two phase mixture model. Numerical predictions are compared to the previously published experimental works for pure water and alumina nanofluid and a good agreement is realized. It is observed that the convective heat transfer coefficient for a nanofluid in subcooled flow boiling is higher than that of the base fluid. Heat transfer coefficient increases with increasing of nanoparticles concentration. However, the effect of nanoparticle concentration on the heat transfer coefficient in the case of high inlet velocity is not significant. On the other hand, in subcooled flow boiling, decreasing the inlet mass flow rate can cause to decrease or increase the heat transfer coefficient which depends on the effect of forced convection and latent heat transport on the overall heat transfer coefficient.

In this study, a blend of polypropylene (PP) and two types of thermoplastic polyolefin elastomers (TPO) were prepared by melt mixing. The TPOs were either ethylene- or propylene-based copolymer. The mechanical response and morphology of the blends were investigated using tensile and impact tests and scanning electron microscopy technique. There was significant increase in the impact strength of the TPO-modified PP, which was an outcome of fine dispersion of TPO inclusions. In particular, the blends containing PP-based TPO exhibited dramatic enhancement in toughness energy as featured by a plastic deformation in tensile test. The brittle-tough transition had several deviations from theoretical models, in which generally the interparticle distance criterion was realized as a single parameter, only controlled the transition of brittle to tough behavior. Moreover, the brittle-tough transition in tensile and impact mode tests was not coincident in the blend with a broad distribution of interparticle distance. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 44068.

Differentiation abnormalities are a hallmark of tuberous sclerosis complex (TSC) manifestations; however, the genesis of these abnormalities remains unclear. Here we report on mechanisms controlling the multi-lineage, early neuronal progenitor and neural stem-like cell characteristics of lymphangioleiomyomatosis (LAM) and angiomyolipoma cells. These mechanisms include the activation of a previously unreported Rheb-Notch-Rheb regulatory loop, in which the cyclic binding of Notch1 to the Notch-responsive elements (NREs) on the Rheb promoter is a key event. This binding induces the transactivation of Rheb. The identified NRE2 and NRE3 on the Rheb promoter are important to Notch-dependent promoter activity. Notch cooperates with Rheb to block cell differentiation via similar mechanisms in mouse models of TSC. Cell-specific loss of Tsc1 within nestin-expressing cells in adult mice leads to the formation of kidney cysts, renal intraepithelial neoplasia, and invasive papillary renal carcinoma., Tuberous sclerosis complex (TSC) is a rare genetic condition causing tumours with differentiation abnormalities; however the molecular mechanisms causing these defects are unclear. Here the authors show that Notch cooperates with Rheb to block cell differentiation forming a regulatory loop that could underlie TSC tumorigenesis.

In this study, variations of local heat transfer coefficient are obtained in subcooled flow boiling conditions for water/TiO2 nanofluid in a vertical and horizontal tube. The results for the base fluid are compared with the predictions of the well known Shah correlation and Gnielinski formula for laminar and turbulent flows for single-phase forced convection and also with Chen correlation for subcooled flow boiling. A good agreement between the results is realized. At the subcooled regime, heat transfer coefficient of nanofluid is less than that of the base fluid and it decreases by increasing nanoparticle concentration for both of the channels; however, addition of the nanopraticles into the fluid causes that the vapor volume fraction increases.

An inverse analysis is employed to estimate the required input on the heater surface (i.e., heater power distribution) that produces the desired temperature and heat flux distribution over the design surface. The inverse problem is formulated as an optimization problem for minimization of an objective function, which is defined by the sum of the square of the difference between estimated and desired heat fluxes distribution over the design surface. The optimization problem is solved using the conjugate gradient method through an iterative procedure. The modified discrete ordinates method is used to solve the radiative transfer equation in an absorbing, emitting, and isotropic/anisotropic scattering medium. Enclosures with diffuse and gray walls are considered. Radiation is assumed to be the dominant mode of heat transfer. First, the performance and accuracy of the present method for solving direct and inverse problems are checked. Then, the effect of some thermophysical properties, such as extinction coef...

PurposeThe solution of radiative heat transfer problems in participating media is often obtained using the standard discrete ordinates method (SDOM). This method produces anomalies caused by ray effects if radiative boundary conditions have discontinuities or abrupt changes. Ray effects may be mitigated using the modified discrete ordinates method (MDOM), which is based on superposition of the solutions obtained by considering separately radiation from the walls and radiation from the medium. The purpose of this paper is to study the role of ray effects in combined conduction‐radiation problems and investigate the superiority of the MDOM over SDOM.Design/methodology/approachThe MDOM has been used to calculate radiative heat transfer in irregular geometries using body‐fitted coordinates. Here, the blocked‐off region concept, originally developed in computational fluid dynamics, is used along with the finite volume method and SDOM or MDOM to solve combined conduction‐radiation heat transport problems in irregular geometries. Enclosures with an absorbing, emitting and isotropically or anisotropically scattering medium are analyzed.FindingsThe results confirm the capability of the MDOM to minimize the anomalies due to ray effects in combined heat transfer problems, and demonstrate that MDOM is more computationally efficient than SDOM.Originality/valueThe paper demonstrates the application of MDOM to combined conduction‐radiation heat transfer problems in irregular geometries using blocked‐off method.

This paper develops a test for comparing treatment effects when observations are missing at random for repeated measures data on independent subjects. It is assumed that missingness at any occasion follows a Bernoulli distribution. It is shown that the distribution of the vector of linear rank statistics depends on the unknown parameters of the probability law that governs missingness, which is absent in the existing conditional methods employing rank statistics. This dependence is through the variance–covariance matrix of the vector of linear ranks. The test statistic is a quadratic form in the linear rank statistics when the variance–covariance matrix is estimated. The limiting distribution of the test statistic is derived under the null hypothesis. Several methods of estimating the unknown components of the variance–covariance matrix are considered. The estimate that produces stable empirical Type I error rate while maintaining the highest power among the competing tests is recommended for implementati...

PurposeThe purpose of this paper is to present, for the first time, a mathematical model for a piston skirt in mixed lubrication with respect to applying a smart fluid in lubrication. In this way, the smart fluid, as a lubricant with controlled variable viscosity, is proposed and applied to minimize the power loss in the interaction between liner and skirt.Design/methodology/approachBased on signal processing, the relationships between viscosity of lubricant and the friction loss, the hydrodynamic and contact friction force consequently are found, as part of an effective approach to acquire the function of variable viscosity.FindingsIt is shown that hydrodynamics and contact friction forces can be controlled and minimized by using the variable viscosity signal with the optimized viscosity signal technique.Originality/valueIn this paper, a mathematical model for a piston skirt in mixed lubrication with respect to applying a smart fluid in lubrication is presented for the first time.

The solar chimney which has been built in Kerman (Kerman city-Iran) is a small scale electrical power plant. The chimney of this unit has 60 m height and 3 m diameter. The collector of this unit is 40 m × 40 m square. To reach nominal power of this unit of power plant, parameters which are effective in optimization are studied. In this regard, we deliberate and propose suggestions to maximize usage of solar energy and kinetic energy. The calculation of maximum power is one of the objectives of this study, so the paper present economic analysis for Kerman solar chimney. A home code has been written for this modeling, in MATLAB.

A methodology for solving inverse radiation heat transfer problems when design variables are discrete is presented. An optimization method is used to find the best number and location of discrete equal power heaters to produce the desired temperature and heat flux distribution over the design surface of radiant enclosures. The medium is assumed to be absorbing, emitting, and scattering. Isothermal and radiative equilibrium media are considered. The modified discrete ordinates method, that mitigates ray effects caused by discontinuities or abrupt changes of wall temperature, is employed to solve the radiative transfer equation. The micro genetic algorithm is used to minimize objective function.

The standard discrete ordinates method (SDOM) produces anomalies caused by ray effects if the temperature of the walls has discontinuities or abrupt changes. Ray effects may be mitigated using the modified discrete ordinates method (MDOM), which is based on superposition of the solutions obtained by considering separately radiation from the walls and radiation from the medium. The MDOM has been used to calculate radiative heat transfer in irregular geometries using body-fitted coordinates. Here, the blocked-off region concept is used along with the MDOM to solve radiative transfer problems in irregular geometries. Two-dimensional irregular enclosures with curved boundaries, obstacles or radiation shields and containing a participating medium are considered. The accuracy of the results calculated using the SDOM and the MDOM is assessed by comparing the predictions with those obtained by other researchers. The results confirm the capability of the MDOM to minimize the anomalies due to ray effects in various situations. It is concluded that the blocked-off region concept can be recommended as a good option to solve radiative transport problems in irregular geometries.

This paper consists of two parts. In the first part we present a new primal-dual feasible interior-point algorithm for solving monotone linear complementarity problems (LCP). Since the algorithm uses only full-Newton steps, it has the advantage that no line-searches are needed. It is proven that the number of iterations of the algorithm is O ( n log n e ) , which coincides with the well-known best iteration bound for LCP. In the second part, we generalize an infeasible interior-point method for linear optimization introduced by Roos (2006) [15] to LCP. Two types of full-Newton steps are used, feasibility steps and (ordinary) centering steps, respectively. The algorithm starts from strictly feasible iterates of a perturbed problem, on its central path, and feasibility steps find strictly feasible iterates for the next perturbed problem. By using centering steps for the new perturbed problem, we obtain strictly feasible iterates close enough to the central path of the new perturbed problem. The starting point depends on two positive numbers ρ p and ρ d . The algorithm terminates either by finding an e -solution or detecting that the LCP problem has no optimal solution with vanishing duality gap satisfying a condition in terms of ρ p and ρ d . The iteration bound coincides with the currently best iteration bound for linear complementarity problems.

Anterior cruciate ligament (ACL) injury continues to be at the forefront of sports injury concerns because of its impact on quality of life and joint health prognosis. One strategy is to reduce the occurrence of this injury by identifying at-risk subjects based on key putative risk factors. The purpose of our study was to develop models that predict the structural properties of a subject's ACL based on the combination of known risk factors. We hypothesized that the structural properties of the ACL can be predicted using a multi-linear regression model based on significant covariates that are associated with increased risk of injury, including age, sex, body size, and ACL size. We also hypothesized that ACL size is a significant contributor to the model. The developed models had predictive capabilities for the structural properties of the ACL: load at failure (R 2 = 0.914), elongation at failure (R 2 = 0.872), energy at failure (R 2 = 0.913), and linear stiffness (R 2 = 0.756). Furthermore, sex, age, body mass, BMI, and height were contributors (p < 0.05) to all predicted structural properties. ACL minimal area was a contributor to elongation, energy at failure, and linear stiffness (p < 0.05), but not to load at failure. ACL volume was also a contributor to elongation and energy at failure (p < 0.05), but not to linear stiffness and load at failure models. ACL length was not a significant contributor to any structural property. The clinical significance of this research is its potential, after continued development and refinement of the model, for application to prognostic studies that are designed to identify individuals at increased risk for injury to the ligament. © 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 29:993-1001, 2011

The cost of mill relining and the influence of the liner profiles on mill performance provide a strong motivation to improve liner selection. However, the capability to predict liner life and progressive profile is poorly developed in the industry. A new model has been developed to predict the rate of liner wear based on the main parameters affecting the wear process such as; ore type, relative velocity between the ore and the liners, liner hardness and friction conditions. The resultant model is capable of determining the wear as a function of mill operating and discharge conditions based on the variation of specific gravity of mill contents, geometrical characteristics of the mill and mill velocity. The results from this model are in good agreement with the measured data from the SAG mill at Sarcheshmeh Copper Complex, Iran.

In mineral processing the mill power plays a major role in the economics of the process and is a critical design criterion. The mill power is influenced by a range of parameters such as: charge and slurry filling, number and geometry of lifters, and mill speed. Deriving the optimum conditions of these parameters should lead to efficient mill operation. Additionally, the optimum utilization of the impact loads that are affected by charge and slurry filling, number of lifters, geometry of lifter and mill speed should result in increased milling efficiency. In this work the influence of these operating parameters were investigated using a laboratory experimental mill. It is found that the power, are affected by number of lifters, lifter height, mill charge and mill speed. Overall the results showed that increasing the mill velocity, number of lifters, and height of lifter and significantly decreasing the mill charge filling results in a higher impact value and impact frequency that may also increase overall efficiency. A simple linear regression relationship has been demonstrated for mill power as a function of lifter spacing (S/H) and mill speed. These parameters give an indication of the possible optimum mill operating conditions in an idealised condition.